Document - Find your way back: Mobility profile mining with constraints

2015

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Find your way back: Mobility profile mining with constraints

Kotthoff L., Nanni M., Guidotti R., Òsullivan B.

Individual Mobility Profiles Constraint Programming Clustering Trajectories

Mobility profile mining is a data mining task that can be formulated as clustering over movement trajectory data. The main challenge is to separate the signal from the noise, i.e. one-off trips. We show that standard data mining approaches suffer the important drawback that they cannot take the symmetry of non-noise trajectories into account. That is, if a trajectory has a symmetric equivalent that covers the same trip in the reverse direction, it should become more likely that neither of them is labelled as noise. We present a constraint model that takes this knowledge into account to produce better clusters. We show the efficacy of our approach on real-world data that was previously processed using standard data mining techniques.

Source: Principles and Practice of Constraint Programming. 21st International Conference, pp. 638–653, Cork, Ireland, 31/09/2015-04/10/2015

Publisher: Springer, Berlin , Germania

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@inproceedings{oai:it.cnr:prodotti:345109,
	title = {Find your way back: Mobility profile mining with constraints},
	author = {Kotthoff L. and Nanni M. and Guidotti R. and Òsullivan B.},
	publisher = {Springer, Berlin , Germania},
	doi = {10.1007/978-3-319-23219-5_44},
	booktitle = {Principles and Practice of Constraint Programming. 21st International Conference, pp. 638–653, Cork, Ireland, 31/09/2015-04/10/2015},
	year = {2015}
}